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Dynamical analysis of mutivariate time series for the early detection of syncope during Head-Up tilt test

Abstract : Syncope is a sudden loss of consciousness. Although it is not usually fatal, it has an economic impact on the health care system and the personal lives of people suffering. The purpose of this study is to reduce the duration of the clinical test (approximately 1 hour) and to avoid patients to develop syncope by early predicting the occurrence of syncope. The entire work fits into a data mining approach involving the feature extraction, feature selection and classification. 3 complementary approaches are proposed, the first one exploits nonlinear analysis methods of time series extracted from signals acquired during the test, the second one focuses on time- frequency (TF) relation between signals and suggests new indexes and the third one, the most original, takes into account their temporal dynamics.
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  • HAL Id : tel-01142153, version 1

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Nadine Khodor. Dynamical analysis of mutivariate time series for the early detection of syncope during Head-Up tilt test. Signal and Image processing. Université Rennes 1, 2014. English. ⟨NNT : 2014REN1S123⟩. ⟨tel-01142153⟩

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